• Dr. SABEEN S
• Dr. Arunadevi R

Abstract This paper introduces the concept of data mining. Basic idea of the GAIT( Graph of Associations in TD) is based on graph SGMAT (Symmetric Graph Matrix). It is a symmetric matrix of graph representing transactions in a transaction database for mining association rules. Association rules are to find relationship in the database. It can even be said, when referring to data mining, people first think of mining association rules. Many algorithms proposed recently have been motivated by FP-Growth (Frequent Pattern Growth) process and uses an FP-Tree (Frequent Pattern Tree) to mine frequent patterns. This paper introduces an algorithm called GAIT (which constructs a graph instead of tree to arrange the items for mining frequent itemsets. The benefit of using graph structure comes in the form of space complexity because graph uses an item as node exactly once rather than two or more times as was done in tree. This algorithm consists of several steps. 1. Scanning the entire transactions from the database only once. 2. Generating a new compressed graph, GAIT, that contains all the transactions in the database with its relationships. 3. Constructing a special type matrix called 2D-SGMAT, Two Dimensional Symmetric Graph Matrix, for the compressed graph, GAIT. 4. Mining all frequent itemsets with its support count. 5. Finally derive all strong association rules satisfying both minimum support threshold and minimum confidence. Here introduce new algorithms for the above five steps.

"GAIT- A POTENTIAL TOOL FOR PROLIFIC MINING OF ASSOCIATION RULES ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.717-724, June 2019, Available :http://www.jetir.org/papers/JETIR1906T93.pdf

"GAIT- A POTENTIAL TOOL FOR PROLIFIC MINING OF ASSOCIATION RULES ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp717-724, June 2019, Available at : http://www.jetir.org/papers/JETIR1906T93.pdf